Potential Use of LiDAR Technology in Forestry Applications

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1 Potential Use of LiDAR Technology in Forestry Applications by Dr. Ahmed Shaker

2 Research Use of mobile and airborne LiDAR technology in engineering applications with a particular interest on land cover classification and object extraction. Develop algorithms to improve the LiDAR data quality: Radiometric Correction Radiometric Normalization Demonstrate the use of single/multi-wavelength LiDAR for: Land Cover Classification Land/Water Delineation Other Applications S2

3 Radiometric Correction cv = σ μ S3

4 Radiometric Normalization Radiometric Normalization To reduce the radiometric misalignment found in overla 1 st Scan 2 nd Scan Laser Pulse 0. Flying Height Overlapping Region Laser Footprint Combined intensity data with line striping noise S4

5 Radiometric Normalization Two radiometrically corrected intensity dataset X A and X B with partial overlap Locate all possible pairwise closest points within a certain threshold Plot the joint intensity-histogram using the pairwise dataset Perform weighted least-squares polynomial fitting Normalize the X B with reference to X A using the fitted function LiDAR data strip X A J Overlap Intensity bin of X A Polynomial Fitting Pairwise Closest Points 0 Intensity bin of X B K Generate Joint-histogram Intensity normalization of X B with reference to X A LiDAR data strip X B S5

6 Examples of Radiometric Correction and Normalization Orion (1500 nm) LiDAR Intensity Data Original Intensity Data Corrected and Normalized Intensity Data S6

7 Examples of Radiometric Correction and Normalization Gemini (1064 nm) LiDAR Intensity Data Original Intensity Data Corrected and Normalized Intensity Data S7

8 Examples of Radiometric Correction and Normalization Gemini (1064 nm) LiDAR Intensity Data Original Intensity Data Corrected and Normalized Intensity Data May 4th, 2016 S8

9 LiDAR Single-Wavelength Classification OI RCI Misclassified as grass Tree OI RCI Dataset 3-classes 4-classes 5-classes OI 60.50% 51.78% 30.50% GCI 60.59% 53.17% 32.08% RCI 68.52% 62.08% 42.08% GC & RCI 69.90% 63.47% 43.27% Misclassified as tree Building Accuracy Improvement Geometric Calibration (GC): 0.1 to 1.6% Radiometric Correction (RC): 8.0 to 11.6% GC & RC: 9.4% to 12.8% S9

10 Multispectral LiDAR Teledyne Optech Parameter Wavelengths Altitudes Scan Angle (FOV) Specification Channel 1 = 1550 nm, Channel 2 = 1064 nm, Channel 3 = 532 nm Topographic: m AGL, all channels Bathymetric: m AGL, channel 3 Programmable; 0-60 max Beam Divergence Channel 1 & 2 = 0.35 mrad, Channel 3 = 0.7 mrad Pulse Repetition Frequency (PRF) khz/channel; 900 khz total Scan Frequency Swath width Point Density Programmable; Hz Up to 115% of AGL Bathymetric: >15 pts/m2 Topographic: >45 pts/m2 S10

11 Multispectral LiDAR Data Classification Digital Surface Model (DSM) 532 nm 1064 nm 1550 nm S11

12 Multispectral LiDAR Data Classification Optech Titan LiDAR data (three wavelengths) Combined intensity images; C1 in red, C2 in green, and C3 in blue Combined intensity images with DSM; DSM in Red, C3 in Green, and C2 in Blue S12

13 Multispectral LiDAR Data Classification Classified Points Classification accuracy of 93% S13

14 Land/Water Delineation - Coastal Area 3D View 2D View Land Water Whitby, ON Aerial Photo Channel 1: 532 nm Channel 2: 1064 nm Channel 3: 1550 nm S14

15 Thank You